Complex Regulatory Network of MicroRNAs, Transcription Factors, Gene Alterations in Adrenocortical Cancer

Zhang, Bo; Xu, Zhinan; Wang, Kunhao; Lu, Tiancheng; Du, Yiqing

doi:10.7314/apjcp.2013.14.4.2265

Cited by 5 publications

(4 citation statements)

References 19 publications

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“…And Tong et al (2012) revealed that mutated gene AKT1, which also has a high potential of being influence on the mechanisms of NB, with other mutated genes play a key role on the key EGFR pathway in human Breast Cancer (BC). Furthermore, we found that this EGFR pathway might have a related network with MYC, which is as a related gene in NB and different-expressed gene in BC (Zhang et al, 2013). These indicated that the same different-expressed miRNAs or genes do have possibilities to influence on different human cancers, which also means it is possible that we can extract several miRNAs and genes having this feature and take some certain measurements to stop them differently expressing in order to helpfully prevent cancers if we sufficiently figure out the inter-relationship of different cancers and combine valid results together.…”

Section: Discussionmentioning

confidence: 83%

Regulatory Network Analysis of MicroRNAs and Genes in Neuroblastoma

Wang

Che

Wang³

et al. 2014

Asian Pacific Journal of Cancer Prevention

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Section: Discussionmentioning

confidence: 83%

Regulatory Network Analysis of MicroRNAs and Genes in Neuroblastoma

Wang

Che

Wang³

et al. 2014

Asian Pacific Journal of Cancer Prevention

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“…Both TFs can potentially bind to the CENPA promoter sequence indicating that they regulate CENPA transcription ( Grant et al, 2013 ). Previous studies have correlated CENPA with poor prognosis in ACC patients and identified E2F2 as an ACC-related TF ( Xia et al, 2019 ; Zhang et al, 2013 ). Although few studies have associated CREB3L3, MYBL2, HOXC11, ZIC2, ZNF282, DNMT1, TCF2, FLK4, and KLF6 with ACC progression ( DiFeo, Martignetti & Narla, 2009 ; Jain, Rechache & Kebebew, 2012 ), there is no evidence linking FOXM1 to ACC.…”

Section: Discussionmentioning

confidence: 99%

A transcription factor signature predicts the survival of patients with adrenocortical carcinoma

Zhao

Liu

2021

PeerJ

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Background Adrenocortical carcinoma (ACC) is a rare endocrine cancer that manifests as abdominal masses and excessive steroid hormone levels and is associated with poor clinical outcomes. Transcription factors (TFs) deregulation is found to be involved in adrenocortical tumorigenesis and cancer progression. This study aimed to construct a TF-based prognostic signature for the prediction of survival of ACC patients. Methods The gene expression profile and clinical information for ACC patients were downloaded from The Cancer Genome Atlas (TCGA, training set) and Gene Expression Omnibus (GEO, validation set) datasets after obtained 1,639 human TFs from a previously published study. The univariate Cox regression analysis was applied to identify the survival-related TFs and the LASSO Cox regression was conducted to construct the TF signature based on these survival-associated TFs candidates. Then, multivariate analysis was used to reveal the independent prognostic factors. Furthermore, Gene Set Enrichment Analysis (GSEA) was performed to analyze the significance of the TFs constituting the prognostic signature. Results LASSO Cox regression and multivariate Cox regression identified a 13-TF prognostic signature comprised of CREB3L3, NR0B1, CENPA, FOXM1, E2F2, MYBL2, HOXC11, ZIC2, ZNF282, DNMT1, TCF3, ELK4, and KLF6. The risk score based on the TF signature could classify patients into low- and high-risk groups. Kaplan-Meier analyses showed that patients in the high-risk group had significantly shorter overall survival (OS) compared to the low-risk patients. Receiver operating characteristic (ROC) curves showed that the prognostic signature predicted the OS of ACC patients with good sensitivity and specificity both in the training set (AUC > 0.9) and the validation set (AUC > 0.7). Furthermore, the TF-risk score was an independent prognostic factor. Conclusions Taken together, we identified a 13-TF prognostic marker to predict OS in ACC patients.

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“…Both TFs can potentially bind to the CENPA promoter sequence indicating that they regulate CENPA transcription 42 . Previous studies have correlated CENPA with poor prognosis in ACC patients and identi ed E2F2 as an ACC-related TF 43,44 . Although few studies have associated CREB3L3, MYBL2, HOXC11, ZIC2, ZNF282, DNMT1, TCF2, FLK4 and KLF6 with ACC progression 45,46 , there is no evidence linking FOXM1 to ACC.…”

Section: Discussionmentioning

confidence: 99%

A Transcription Factor Signature Predicts Prognosis of Patients with Adrenocortical Carcinoma

Zhao

Liu

2021

Preprint

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Background: Adrenocortical carcinoma (ACC) is a rare endocrine cancer that manifests as abdominal masses and excessive steroid hormone levels. Transcription factors (TFs) deregulation is found to be involved in adrenocortical tumorigenesis and cancer progression. This study aimed to construct a TF-based prognostic signature for prediction of survival of ACC patients.Methods: The gene expression profile for ACC patients were downloaded from TCGA and GEO datasets. The univariate Cox analysis was applied to identify survival-related TFs and the LASSO Cox regression was conducted to construct the TF signature. The multivariate analysis was used to reveal the independent prognostic factors.Results: We identified a 13-TF prognostic signature comprised of CREB3L3, NR0B1, CENPA, FOXM1, E2F2, MYBL2, HOXC11, ZIC2, ZNF282, DNMT1, TCF3, ELK4, and KLF6 using the univariate Cox analysis and LASSO Cox regression. The risk score based on the TF-signature could classify patients into low- and high-risk group. Kaplan-Meier analyses showed that patients in the high-risk group had significantly shorter overall survival compared to the low-risk patients. ROC curves showed that the prognostic signature predicted the overall survival of ACC patients with good sensitivity and specificity. Furthermore, the TF-risk score was an independent prognostic factor.Conclusion: Taken together, we identified a 13-TF prognostic marker to predict overall survival in ACC patients.

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Complex Regulatory Network of MicroRNAs, Transcription Factors, Gene Alterations in Adrenocortical Cancer

Cited by 5 publications

References 19 publications

Regulatory Network Analysis of MicroRNAs and Genes in Neuroblastoma

Regulatory Network Analysis of MicroRNAs and Genes in Neuroblastoma

A transcription factor signature predicts the survival of patients with adrenocortical carcinoma

A Transcription Factor Signature Predicts Prognosis of Patients with Adrenocortical Carcinoma

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